{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Finding a Pupil in an Image: OpenCV <img src='data/images/logo.png' width=50 align='left'> \n",
    "\n",
    "\n",
    "author: Thomas Haslwanter\\\n",
    "date: June-2020"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "FindPupil demonstrates how *OpenCV* can be used to find the pupil in an image\n",
    "of the eye. This includes ademonstration of a number of important image\n",
    "processing steps in OpenCV, using Python-CV2.\n",
    "To run, the file `eye.bmp` is required.\n",
    "\n",
    "The following steps are included:\n",
    "\n",
    "- Converting the image to grayscale\n",
    "- Calculating and showing the histogram\n",
    "- Interactively setting the threshold for b/w conversion\n",
    "- Filling holes\n",
    "- Opening the image\n",
    "- Fitting an edge to the pupil\n",
    "\n",
    "Important Notes:\n",
    "* When you run this notebook, openCV often opens the video and image windows in the background, and waits for your response.\n",
    "* To close an OpenCV window, you need to hit the ESC-key."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preliminaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import cv2\n",
    "\n",
    "def nothing(*arg):\n",
    "    ''' A dummy function for the trackbar. '''\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load and Show Image"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note here that to read and show the image, I use the commands from Matplolib. For reading the image, there is not much difference. For showing the image, the Matplotlib command shows the image \"inline\", whereas cv2.imshow creates a named, external window (see below)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x2b3fa259d90>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "img = plt.imread('data\\images\\eye.bmp')\n",
    "#img = cv2.imread('eye.bmp', cv2.CV_LOAD_IMAGE_GRAYSCALE)\n",
    "plt.set_cmap('gray') # Set the colormap to \"gray\"\n",
    "plt.imshow(img)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Show a graylevel histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The \"_\" is a dummy variable to suppress the output\n",
    "_ = plt.hist(img.flatten(),128)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Thresholding, using \"OpenCV\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, let us simply open an image window in OpenCV. Showing simple images in openCV is more involved, as the command \"waitKey\" is required to update the image.\n",
    "\n",
    "**Note:** The following code with generate a OpenCV-window outside this notebook. To close it, press `Esc`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "# Showing the same image in an openCV-window is a bit  tricky:\n",
    "# Note: The following code with generate a OpenCV-window outside this notebook. To close it, press `Esc`\n",
    "\n",
    "cv2.imshow('demo', img)\n",
    "while True:\n",
    "    ch = cv2.waitKey(5)\n",
    "    if ch == 27:\n",
    "        cv2.destroyWindow('demo')\n",
    "        break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, let us generate an interactive image, where wen can adjust a parameter for the image processing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "# Set a threshold, for b/w conversion, using a trackbar\n",
    "cv2.namedWindow('bw')  # First you have to create a named window for OpenCV\n",
    "cv2.createTrackbar('thr', 'bw', 1, 255, nothing)    # dummy function \"nothing\" defined below\n",
    "cv2.setTrackbarPos('thr', 'bw', 85)\n",
    "while True:\n",
    "     thrs = cv2.getTrackbarPos('thr', 'bw')\n",
    "     (thresh, im_bw) = cv2.threshold(img, thrs, 255, cv2.THRESH_BINARY)\n",
    "     cv2.imshow('bw', im_bw)\n",
    "     ch = cv2.waitKey(5)\n",
    "     if ch == 27:\n",
    "         cv2.destroyWindow('bw')\n",
    "         break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x22c9abc34c0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(im_bw)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Remove black border, Fill holes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x22c9ad30340>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Remove the black border\n",
    "h,w = img.shape\n",
    "mask = np.zeros( (h+2,w+2), dtype=np.uint8)\n",
    "cv2.floodFill(im_bw, mask, (1,1), 255)\n",
    "    \n",
    "# Fill the holes\n",
    "wHoles = im_bw.copy()\n",
    "# Note that the mask has to be 2 pixels larger than the image!\n",
    "mask = np.zeros( (h+2,w+2), dtype=np.uint8)\n",
    "cv2.floodFill(wHoles, mask, (1,1), 0)\n",
    "im_bw[wHoles==255] = 0\n",
    "plt.imshow(im_bw)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Eliminate Eyelid, by \"closing\" the image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x22c9e24e4c0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from skimage.morphology import disk\n",
    "strEl = disk(10)  # structural Element\n",
    "closed = cv2.morphologyEx(im_bw, cv2.MORPH_CLOSE, strEl)\n",
    "plt.imshow(closed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Edgy Finish"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x22c9e2a3700>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "thrs1 = 1000\n",
    "thrs2 = 1000\n",
    "edge = cv2.Canny(closed, thrs1, thrs2, apertureSize=5)\n",
    "plt.imshow(edge)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[5_ImgProc_Example_skimage](5_ImgProc_Example_skimage.ipynb)<img src=\"data\\images\\Forward_Backward.png\" align='middle'>[6_Events](6_Events.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.9"
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  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
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   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
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    "lenType": 16,
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   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
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     "varRefreshCmd": "print(var_dic_list())"
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     "varRefreshCmd": "cat(var_dic_list()) "
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   "types_to_exclude": [
    "module",
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    "builtin_function_or_method",
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    "_Feature"
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 "nbformat": 4,
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